Analytical Approach

Analytical Approach

Data Analytical Methods and Techniques

Actionable Insights

Analytics and data science go hand-in-hand, with analysis unearthing and interpreting meaningful patterns within data. The field of analytics combines statistics, computer programming and operations research. Results from data analysis can guide decision-making, and it is frequently used by businesses to assess, predict and improve performance.

Understanding the drivers behind, gathering and deciphering data are as important as the insights themselves. Knowing what needs to be achieved, and what Key Performance Indicators success will be measured against, is fundamental to the effective roll out of data analytics solutions.

Our Approach and Methodology

CHANGEPOND harnesses emerging technologies to refine our service offerings and help customers address their 5 “V”s of Big Data.

5 “V”s of Big Data

Volume

  • Terabytes
  • Records/Arch
  • Transactions
  • Tables, Files

Velocity

  • Batch
  • Real/Near-time
  • Processes
  • Streams

Variety

  • Structures
  • Unstructured
  • Multi-factor
  • Probabilistic

Value

  • Statistical
  • Events
  • Correlations
  • Hypothetical

Veracity

  • Trustworthiness
  • Authenticity
  • Origin, Reputation
  • Availability, Accountability

Our methodology takes care of getting a detailed insight into who the audience of the project is , before it starts thus , defining which channels are used to gather data and how the feedback from these channels can be combined for the most effective and accurate analysis.

Business methodology

CHANGEPOND’s Data Solutions Eco-System

Our Data Solutions and Analytics Services help clients manage their complete information lifecycle from transaction systems through data migration, data management and analysis to visualize information by creating “value” to their data. Our services enable clients to maximize what can be done with data through quality information, ably supported by the best techniques for dealing with it.

  • Business Understanding
  • Data Understanding
  • Data Modeling
  • Implementation
  • DevOPs
  • Gateway / Middleware
  • IoT Handler & Storage
  • Enterprise Systems
  • Common Functions
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1

Raw Data Storage

  • Handles Structured and Unstructured data
  • Hadoop – based
  • Map reduce Algorithms
2

Data Ware house

  • Handles Only Structured data
  • Massively Parallel Processing (MPP)
  • Column Based
  • Cloud Service
3

Visualization and Analytics

  • Handles Structured Data
  • Visualization and reporting
4

Business Applications

  • Real Time Applications
  • Recommendation Engines
  • Machine Learning
  • No SQL Solutions

Data Solutions Technology Capabilities

Our technology capabilities span the entire spectrum of the “edge to enterprise” value chain.